The official exam

Questions

53

Time

120 minutes

Fee

US$125

Passing score

720 on a 100-1000 scale

Valid for

12 months

Format

Multiple-choice and multiple-response

Delivery

Proctored online or at a test center

As published by Anthropic in exam guide 1.0 (July 2026); checked 9 August 2026. Read the official exam guide

Who it's for

Software engineers, AI engineers, and technical builders with Python or TypeScript experience and working knowledge of REST APIs and command-line tools.

• One to five years of software-engineering experience
• At least six months with Claude or comparable LLM systems
• Fluency with REST APIs, JSON, asynchronous code, and CLI tools
• Working knowledge of agents, context management, and MCP

What the exam covers

• Agents and Workflows14.7%
• Applications and Integration33.1%
• Claude Code3.1%
• Eval, Testing, and Debugging2.6%
• Model Selection and Optimization16.8%
• Prompt and Context Engineering11%
• Security and Safety8.1%
• Tools and MCPs10.6%

Practice exams

Original questions in the official format, timed like the real thing, with a breakdown by exam domain and an explanation for every answer. Start with the diagnostic.

• Developer Foundations Diagnostic16 questions, 30 minutesFree
• Developer Foundations Full Mock53 questions, 120 minutes

Lessons

1. 1Study the Decisions, Not the VocabularyA certification blueprint is a map of decisions a competent practitioner can defend. Treat it as a list of terms and you will study the least useful part of the exam.LearnPython1.5 h
2. 2Choose the Smallest Surface That Can Carry the WorkProduct selection is architecture at knowledge-work scale. The wrong surface can make correct output stale, unreviewable, or needlessly expensive.LearnPython1.5 h
3. 3Spend Capability Where Failure Is ExpensiveModel selection is not a ranking exercise. It is an allocation problem across quality, latency, context, and cost.LearnPython1.5 h
4. 4Turn a Request Into a Testable ContractA strong prompt does not merely describe what to write. It makes success observable before generation begins.LearnPython1.5 h
5. 5Put Each Fact in the Right Kind of ContextContext is temporary attention. Knowledge is maintained evidence. Memory is continuity. Caching is reuse. Mixing them creates confident stale answers.LearnPython2 h
6. 6Validate the Claim, Not the ConfidenceFluency is presentation quality. Validation is evidence that the output can safely do its job.LearnPython2 h
7. 7The Messages API Is a State MachineThe API does not remember your conversation. Your application does, and one misplaced content block can break the entire loop.BuildPython2 h
8. 8Structured Output Is an Untrusted ContractValid JSON is not a valid business decision. Parse the bytes, validate the shape, verify the meaning, then permit the action.BuildPython1.5 h
9. 9A Tool Loop Is Controlled DelegationClaude may propose an action. Your application validates the request, grants the capability, observes the result, and decides whether the loop continues.BuildPython2 h
10. 10MCP Separates Capability From HostBuild a narrow, stateless MCP server whose contract can be discovered, cached, invoked, and scaled without hidden connection state.BuildPython2 h
11. 11The Agent SDK Is a Harness, Not PermissionAn agent becomes dependable when the loop, tools, context, hooks, and termination policy are explicit enough to inspect and constrain.LearnPython2.5 h
12. 12Security Lives Outside the PromptThe model can recommend a safe action. Only deterministic controls can make an unsafe action impossible.BuildPython2 h
13. 13Evals Turn Agent Behavior Into Engineering EvidenceA trace tells you what happened. An eval tells you whether it was acceptable. A regression gate keeps the next change from quietly making it worse.BuildPython2 h
14. 14Claude Code Scales Through Shared ConstraintsA team does not need one giant prompt. It needs a small project contract, reusable procedures, deterministic checks, and versioned configuration.LearnPython3 h
15. 15Ship a Claude Application You Can DefendThe capstone is not a chatbot demo. It is a bounded application with a wire contract, security boundary, eval evidence, and recovery plan.BuildPython4 h

Study plans

Go deeper in the Academy

• The Agent Loop (Phase 14): Build the loop before using an SDK
• Claude Agent SDK (Phase 14): Go deeper on the production SDK surface
• Tool Schema Design (Phase 13): Design clear, testable tool contracts
• Building an MCP Server (Phase 13): Implement the server boundary end to end
• Prompt Injection Defense (Phase 14): Threat-model untrusted instructions
• Eval-Driven Agent Development (Phase 14): Use trajectories and final state as release evidence

Katalock's Claude certification prep is independent study material based on Anthropic's public exam guides. It is not affiliated with, endorsed by or authorised by Anthropic, does not contain live exam questions, and cannot guarantee a pass. Practice scores are raw percentages. They are not Anthropic's 100 to 1,000 scaled score and can't predict an official result.